A Multi-layered Quantitative In Vivo Expression Atlas of the Podocyte Unravels Kidney Disease Candidate Genes

Markus M. Rinschen, Markus Gödel, Florian Grahammer, Stefan Zschiedrich, Martin Helmstädter, Oliver Kretz, Mostafa Zarei, Daniela A. Braun, Sebastian Dittrich, Caroline Pahmeyer, Patricia Schroder, Carolin Teetzen, Heon Yung Gee, Ghaleb Daouk, Martin Pohl, Elisa Kuhn, Bernhard Schermer, Victoria Küttner, Melanie Boerries, Hauke BuschMario Schiffer, Carsten Bergmann, Marcus Krüger, Friedhelm Hildebrandt, Joern Dengjel, Thomas Benzing, Tobias B. Huber

Research output: Contribution to journalArticlepeer-review

65 Citations (Scopus)

Abstract

Damage to and loss of glomerular podocytes has been identified as the culprit lesion in progressive kidney diseases. Here, we combine mass spectrometry-based proteomics with mRNA sequencing, bioinformatics, and hypothesis-driven studies to provide a comprehensive and quantitative map of mammalian podocytes that identifies unanticipated signaling pathways. Comparison of the in vivo datasets with proteomics data from podocyte cell cultures showed a limited value of available cell culture models. Moreover, in vivo stable isotope labeling by amino acids uncovered surprisingly rapid synthesis of mitochondrial proteins under steady-state conditions that was perturbed under autophagy-deficient, disease-susceptible conditions. Integration of acquired omics dimensions suggested FARP1 as a candidate essential for podocyte function, which could be substantiated by genetic analysis in humans and knockdown experiments in zebrafish. This work exemplifies how the integration of multi-omics datasets can identify a framework of cell-type-specific features relevant for organ health and disease. The podocyte forms the most outer and essential part of the renal filter and restricts the passage of proteins from blood to urine. Rinschen et al. combine deep proteomic and transcriptomic data with protein dynamics from native mouse podocytes to reveal insights into podocyte biology and to identify candidate disease genes.

Original languageEnglish
Pages (from-to)2495-2508
Number of pages14
JournalCell Reports
Volume23
Issue number8
DOIs
Publication statusPublished - 2018 May 22

Bibliographical note

Funding Information:
We thank Ruth Herzog, Charlotte Meyer, Temel Kilic, Valerie Oberüber, Christine Gretzmeier, and Barbara Joch for expert technical assistance and all members of our laboratories for helpful discussions. This study was supported by the German Research Foundation (DFG) UoC postdoctoral grant and a DFG fellowship (Ri 2811/1-1) (to M.M.R.), CRC 1140 (to F.G., C.B., and T.B.H.), KFO 329 (to T.B. and B.S.) CRC 992 (to T.B.H.), the Heisenberg program (to T.B.H.), and HU 1016/5-1 and HU 1016/8-1 (to T.B.H.); by a European Research Council (ERC) grant (to T.B.H.) and by the H2020-IMI2 Consortium BEAt-DKD (115974 to T.B.H.); by BMBF STOP-FSGS 01GM1518C (to T.B.H.); by the Excellence Initiative of the German Federal and State Governments (BIOSS) (to T.B.H.) and the Freiburg Institute for Advanced Studies (FRIAS) (to T.B.H.); and by the Else Kröner Fresenius Stiftung, NAKSYS (to T.B.H.). C.B. was supported by the Federal Ministry of Education and Research (BMBF, 01GM1515C, Project 2.3). M.B. is funded by BMBF within the framework of the e:Med Research and Funding Concept (DeCaRe, FKZ 01ZX1409B) and by DFG Collaborative Research Center (CRC) 850, Projects Z1 and C9. H.B. acknowledges funding through the DFG Excellence Cluster EXC 306. M.S. was supported by the Fritz Thyssen Foundation (10.16.2.026MN) and BMBF Grant 01GM1518A. F.H. was supported by the NIH (R01-DK076683). M.G. was supported by the German Society of Nephrology (Forschungsstipendium der Deutschen Gesellschaft für Nephrologie 2012). We thank the Yale Center for Mendelian Genomics (U54HG006504) for whole-exome sequencing.

Funding Information:
We thank Ruth Herzog, Charlotte Meyer, Temel Kilic, Valerie Oberüber, Christine Gretzmeier, and Barbara Joch for expert technical assistance and all members of our laboratories for helpful discussions. This study was supported by the German Research Foundation (DFG) UoC postdoctoral grant and a DFG fellowship ( Ri 2811/1-1 ) (to M.M.R.), CRC 1140 (to F.G., C.B., and T.B.H.), KFO 329 (to T.B. and B.S.) CRC 992 (to T.B.H.), the Heisenberg program (to T.B.H.), and HU 1016/5-1 and HU 1016/8-1 (to T.B.H.); by a European Research Council (ERC) grant (to T.B.H.) and by the H2020-IMI2 Consortium BEAt-DKD ( 115974 to T.B.H.); by BMBF STOP-FSGS 01GM1518C (to T.B.H.); by the Excellence Initiative of the German Federal and State Governments (BIOSS) (to T.B.H.) and the Freiburg Institute for Advanced Studies (FRIAS) (to T.B.H.); and by the Else Kröner Fresenius Stiftung , NAKSYS (to T.B.H.). C.B. was supported by the Federal Ministry of Education and Research ( BMBF , 01GM1515C , Project 2.3 ). M.B. is funded by BMBF within the framework of the e:Med Research and Funding Concept ( DeCaRe , FKZ 01ZX1409B ) and by DFG Collaborative Research Center (CRC) 850 , Projects Z1 and C9 . H.B. acknowledges funding through the DFG Excellence Cluster EXC 306 . M.S. was supported by the Fritz Thyssen Foundation ( 10.16.2.026MN ) and BMBF Grant 01GM1518A . F.H. was supported by the NIH ( R01-DK076683 ). M.G. was supported by the German Society of Nephrology (Forschungsstipendium der Deutschen Gesellschaft für Nephrologie 2012) . We thank the Yale Center for Mendelian Genomics ( U54HG006504 ) for whole-exome sequencing.

Publisher Copyright:
© 2018 The Authors

All Science Journal Classification (ASJC) codes

  • Biochemistry, Genetics and Molecular Biology(all)

Fingerprint

Dive into the research topics of 'A Multi-layered Quantitative In Vivo Expression Atlas of the Podocyte Unravels Kidney Disease Candidate Genes'. Together they form a unique fingerprint.

Cite this